Answered By: Danielle Abrahamse
Last Updated: Jun 17, 2021     Views: 36

Metadata is 'data about data' or 'data describing other data'. In a data curation context, metadata can be divided into simple metadata that aids findability, such as keywords and disciplinary categorisation; and more in-depth metadata that enhances the possibility of the data being reused, such as detailed descriptions or abstracts, inclusion of details on the instrumentation used to collect the data (such as interview schedules, survey questionnaires, instrument specifications), and codebooks or variable lists.

The more supporting information you provide, the richer the metadata you create will be. This of course needs to be balanced against your time constraints.

It is vital that research data is accompanied by sufficient metadata (such as keywords and other descriptive information about the dataset) for it to be understandable, retrievable and reusable in the long term. Various disciplines have published guidelines for what metadata should accompany their datasets - consider doing some research to see if there are guidelines for your subject area.

The following resources may provide some support in conceptualising your project’s metadata activity: